YongZhang's Page

This project focuses on scalable data processing and query performance optimisation. It uses Snowflake for data warehousing, GCP Cloud Functions for serverless compute, and Apache Kafka for real-time data streaming. It leverages the serverless capabilities of the systems for scalability and performance.

A visualizer for queries - Hyper, Postgres, Tableau

torch-like convolution over binary trees

platform for benchmarking hint-based optimisation approaches

Instructional materials (course files) for the BBT3104 course (Advanced Database Systems) and the MIT8107 course (Advanced Database Systems). Topic: Query Optimization. Based on the IMDb dataset using PostgreSQL and the Join Order Benchmark (JOB).

Add efficient pipelining, batching, and caching to any data source

Run the PostgreSQL Explain Visualizer 2 (pev2) from the command line.

A lightweight RL environment for query optimization.

Partitioning tool for PostgreSQL

This repository contains a project that involves creating and managing a MySQL database using the IMDb dataset. It includes scripts and instructions for setting up the database, importing the IMDb dataset, and performing various queries to extract meaningful insights from the data.

An advanced distributed knowledge fabric for intelligent document processing, featuring multi-document agents, optimized query handling, and semantic understanding.

Code for "Text-Video Retrieval with Global-Local Semantic Consistent Learning"

The program is designed to create an index from a large collection of documents efficiently and do query processing.

A collection of tutorials on computer fundamentals

Enhance the performance and cost-efficiency of large-scale Retrieval Augmented Generation (RAG) applications. Learn to integrate vector search with traditional database operations and apply techniques like prefiltering, postfiltering, projection, and prompt compression.

Get Visual MySQL EXPLAIN plans that are understandable for humans

🌟Welcome to a curated 📚 collection 📚 of solved 🛠️ MySQL 💾 interview 💬 problems ❓ from LeetCode 💡. 📊🔍 This section 📚 showcases 🔍 key questions ❓ and their solutions 💡, providing 📊 a valuable 🛠️ resource 📚 for anyone 💬 preparing 🛠️ for SQL 💾 interviews 💬. 🚀

postgres query execution plan analysis and benchmarking

Advanced SQL, covering Oracle PL/SQL and PostgreSQL PL/pgSQL with phases on using procedures, functions, triggers, query optimizations, packages, and Docker server setup 💡